Receiver-operating characteristic curve analysis in diagnostic, prognostic and predictive biomarker research.
ABSTRACT From a clinical perspective, biomarkers may have a variety of functions, which correspond to different stages in the disease development, e.g. in the progression of cancer. Biomarkers can assist in the care of patients for screening, diagnosis, prognosis, prediction and surveillance. Fundamental for the use of biomarkers in all situations is biomarker accuracy - the ability to correctly classify one condition and/or outcome from another. Receiver-operating characteristic (ROC) curve analysis is a useful tool in assessment of biomarker accuracy. Its advantages include testing accuracy across the entire range of scores and thereby not requiring a predetermined cut-off point, in addition to easily examined visual and statistical comparisons across tests or scores, and, finally, independence from outcome prevalence. Further, ROC curve analysis is a useful tool for evaluating the accuracy of a statistical model that classifies subjects into one of two categories. Diagnostic models are different from predictive and prognostic models in that the latter incorporate time-to-event analysis, for which censored data may pose a weakness of the model, or the reference standard. However, with the appropriate use of ROC curves, investigators of biomarkers can improve their research and presentation of results. ROC curves help identify the most appropriate classification rules. ROC curves avoid confounding resulting from varying thresholds with subjective ratings. The ROC curve results should always be put in perspective, because a good classifier does not guarantee the eventual clinical outcome, in particular for time-dependant events in screening, prediction, and/or prognosis studies where particular statistical precautions and methods are needed.
- SourceAvailable from: Davide Cacchiarelli[Show abstract] [Hide abstract]
ABSTRACT: Dystrophin absence in Duchenne muscular dystrophy (DMD) causes severe muscle degeneration. We describe that, as consequence of fibre damage, specific muscle-miRNAs are released in to the bloodstream of DMD patients and their levels correlate with the severity of the disease. The same miRNAs are abundant also in the blood of mdx mice and recover to wild-type levels in animals 'cured' through exon skipping. Even though creatine kinase (CK) blood levels have been utilized as diagnostic markers of several neuromuscular diseases, including DMD, we demonstrate that they correlate less well with the disease severity. Although the analysis of a larger number of patients should allow to obtain more refined correlations with the different stages of disease progression, we propose that miR-1, miR-133, and miR-206 are new and valuable biomarkers for the diagnosis of DMD and possibly also for monitoring the outcomes of therapeutic interventions in humans. Despite many different DMD therapeutic approaches are now entering clinical trials, a unifying method for assessing the benefit of different treatments is still lacking.EMBO Molecular Medicine 03/2011; 3(5):258-65. · 7.80 Impact Factor
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ABSTRACT: The association between DNA methylation status and embryogenic competency in oil palm tissue culture was examined through Representational Difference Analysis (RDA) approach, using methylation-sensitive restriction endonucleases. “Difference Products” (DPs) of RDA derived from palms of similar genetic backgrounds but exhibiting different embryogenesis rates during the regeneration process were isolated. The DPs were sequenced using a pyrosequencing platform. To our knowledge, this is the first study profiling partial HpaII methylation sites in oil palm young leaf tissues which are potentially associated with embryogenic amenability through a genomic subtractive approach. Quantitative real-time PCR analysis demonstrated that the methylation status of a novel fragment, EgNB3, was higher in highly embryogenic leaf explants compared to low embryogenesis rate materials. These differences are likely to be contributed by the 5′-mCCGG-3′ and/or 5′-mCmCGG-3′ methylation patterns. Our data suggest that the differentially methylated site in EgNB3 has potential as a molecular biomarker for the screening of oil palm leaf explants for their embryogenic potentials.Tree Genetics & Genomes 08/2013; 9(4):1099. · 2.40 Impact Factor
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ABSTRACT: Epstein-Barr virus (EBV)-mediated lymphomagenesis in the setting of HIV infection has been widely accepted. However, little is known about how EBV impacts prognosis. We investigated the hypothesis that EBV infection is associated with expression of specific B-cell oncogenic markers in HIV-related diffuse large B-cell lymphoma (DLBCL) and examined the prognostic use of detecting EBV infection. HIV-related DLBCL cases diagnosed between 1996 and 2007 within Kaiser Permanente California were identified. Immunohistochemical staining was used to analyze the expression of selected markers that are cell-cycle regulators, B-cell activators, and antiapoptotic proteins among others. EBV infection was determined by in situ hybridization of EBV RNA. Correlations between EBV and marker expression were examined using Spearman correlation coefficient. The prognostic use of EBV status was examined in multivariable Cox model adjusting for International Prognostic Index (IPI). Receiver-operating characteristics (ROC) analysis was used to evaluate improvement in model discrimination. Seventy HIV-related DLBCL cases were included (31% EBV±). EBV+ tumor was associated with increased expression of BLIMP1 and CD30 and reduced expression of BCL6 and LMO2. EBV+ tumor was independently associated with elevated 2-year overall mortality [HR, 3.3; 95% confidence interval (CI), 1.6-6.6]. Area under the ROC curve showed improved model discrimination when incorporating tumor EBV status with IPI in the prediction model [0.65 vs. 0.74 (IPI only)]. Our results suggest that EBV infection was associated with expression of several tumor markers that are involved in the NF-κB pathway and that detecting tumor EBV status may have prognostic use in HIV-related DLBCLs.Clinical Cancer Research 06/2012; 18(17):4702-12. · 7.84 Impact Factor